Generation and functional analysis of defective viral genomes during SARS-CoV-2 infection

Abstract

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from RNA-seq datasets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hotspots were identified for DVG recombination and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single cell RNA-seq analysis indicated the IFN stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the NGS dataset from a published cohort study and observed significantly higher DVG amount and frequency in symptomatic patients than that in asymptomatic patients. Finally, we observed unusually high DVG frequency in one immunosuppressive patient up to 140 days after admitted to hospital due to COVID-19, first-time suggesting an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection.

Bioinformatic Analysis of Defective Viral Genomes in SARS-CoV-2 and Its Impact on Population Infection Characteristics

“…As reported in experimental studies, the proportion of defective viruses significantly increases with the progression of the infection cycle [26]. Simultaneously, there is a significant decrease in the proportion and absolute concentration of intact RNA viruses.…”

“…One approach is to use DVGs as antiviral drugs, as studies have found that DVGs can significantly inhibit virus replication [24][25]. Sun Yan et al also found significant differences in the content of DVGs among different cell types, and the proportion of DVGs changed significantly with the duration of infection [26]. They also noticed that the content of DVGs in asymptomatic individuals was significantly lower than that in symptomatic individuals.…”

VODKA2: A fast and accurate method to detect non-standard viral genomes from large RNA-seq datasets

“…1F). It has become clear over the past decade that nsVGs play a crucial role in virus pathogenesis (Felt et al, 2021;Penn et al, 2022;Vasilijevic et al, 2017;Vignuzzi and Lopez, 2019;Zhou et al, 2022). As a consequence, there has been a big push in the nsVG field to develop NGS/bioinformatics approaches that are more sensitive, less biased, and more accurate, such as DI-tector (Beauclair et al, 2018), DVG-Profiler (Bosma et al, 2019), DG-Seq (Boussier et al, 2020), ViReMa (Jaworski and Routh, 2017;Routh and Johnson, 2014;Sotcheff et al, 2023) and DVGfinder (Olmo-Uceda et al, 2022).…”

Accumulation dynamics of defective genomes during experimental evolution of two betacoronaviruses

“…The interferon response has been identified as key in infections in which the presence of DVGs impacts the severity of symptoms (Zhou et al, 2023), or in which infection does not resolve but becomes chronic (Mura et al 2017;Vignuzzi and López 2019;Wignall-Fleming et al 2020).…”